Energy

Intel, Microsoft, and others PC power players like to brag about how fast their computers are by drawing comparisons to "five-year-old PCs." But does this obsession with performance miss a more important message? We think it does, and there are many more reasons to buy a modern PC than just raw speed. Interactivity, convenient security, ease of use--these are critical features that don't appear on spec lists. Even a modern PC's sheer portability may not be immediately apparent.

Digital transformations are slated to transform the industry by reducing expenditures, improving operations, and providing a granular view of workflows enabling more effective decision-making. In the heart of all these digitization efforts in our industry lies machine learning. Machine learning enables us to build complex models on the data collected, leading to better decisions. In the simplest terms, it is a form of artificial intelligence (AI) which is designed to learn on its own or become better as it is fed more data. These algorithms have the potential to revolutionize our workflow in the future when the applicability of AI increases.

An era of rapid evolution of structures and devices driven by new capabilities in machine learning, nanoscale experiments, and economic modeling is unfolding, MIT materials researchers revealed during the annual Industrial Liaison Program (ILP) Research and Development Conference. Pointing to progress in areas as diverse as biomedical devices, computing, and energy, Carl Thompson, director of the MIT Materials Research Laboratory and the Stavros Salapatas Professor of Materials Science and Engineering, noted the convergence of advances in nanoscale imaging and computerized prediction of materials structure and behavior with analysis of the likelihood of success in the marketplace. A longstanding problem with green energy sources, including solar and wind, is their power production varies widely and is often mismatched to demand. Thompson noted the work of Jessika Trancik, an associate professor of energy studies who has identified the economic value of various energy storage methods based on their relative costs. These methods include compressed air, pumped water, and vanadium-based flow batteries, in addition to traditional cell-type batteries such as nickel-cadmium, lithium ion and sodium-sulfur combinations.

Samsung has unveiled the 2019 edition of its high-end convertible, the Notebook 9 Pen. Aimed at creative professionals, it offers a new and improved built-in S Pen that works on a device that can be used as a laptop or tablet. The 2-in-1 is available with a 13-inch or 15-inch full HD LCD screens, both of which come with a dark-blue aluminum finish, 16GB of RAM, 512GB of storage, and Intel's 8th generation Core i7 processors. The 15-inch model is a new option for the Notebook Pen. They also sport a backlit keyboard and feature facial and fingerprint recognition.

The robot will go through an initial assessment phase to check on its overall health and the health of its instruments before it can move on to the deployment phase. Then, once its finally time to deploy its suite of instruments, that process alone is expected to take two to three months. InSight will place its seismometer, and only once the team is happy with its location and initial operations will it return to the deck to get its wind and thermal shields, which will sit atop the seismometer for protection. The lander will then pick up the heat probe to bring to the surface, before beginning its historic dig. Eventually, once it's all settled in, Barrett says we'll be'sitting back listening for Mars quakes.'

Chris Lister, vice president of operations of the Tesla Gigafactory, provides insight during a tour on Dec. 3, 2018. Big numbers are one way to appreciateTesla's gargantuan Nevada Gigafactory. Operating 24-hours per day in shifts, workers produce enough battery packs and drive units in a week to power 5,300 of Tesla's Model 3 sedans. Tesla says at 5.4 million square feet, roughly equivalent to 50 Home Depot stores, the factory is just 30 percent of its potential size and is already producing more batteries than all other carmakers combined. With more than 7,000 Tesla workers, the factory is responsible for increasing manufacturing employment in the Reno-Sparks area by 55 percent since 2014, according to the Governor's Office of Economic Development.

Fifty years ago today, Doug Engelbart showed 2,000 people a preview of the future. Engelbart gave a demonstration of the "oN-Line System" at the Fall Joint Computer Conference in San Francisco on Dec. 9, 1968. The oN-Line System was the first hypertext system, preceding the web by more than 20 years. But it was so much more than that. When Engelbart typed a word, it appeared simultaneously on his screen in San Francisco and on a terminal screen at the Stanford Research Institute in Menlo Park.

This will enable more people in your organization to leverage machine learning and most importantly allow domain experts to rapidly prototype ML solutions and validate their hypothesis before involving data scientists. If you are an experienced data scientist, automated ML will let you improve productivity and save time by eliminating the need to manually perform the tedious and repetitive tasks of feature engineering, algorithm selection and hyperparameter tuning. You can even start by generating a model with automated ML as a starting point and tune it further. Organizations can also use automated ML to benchmark their models. Many Fortune 500 customers are benefiting from using automated ML. These include a global oil & refinery enterprise that's using automated ML to forecast reservoir production and a medical devices company that's using automated ML for predictive maintenance. Automated ML also powers Microsoft Power BI's AI capabilities, where business analysts can build machine learning models without writing a single line of code. Azure Machine Learning service's automated ML capability is based on a breakthrough from our Microsoft Research division and different from competing solutions in the market. The approach combines ideas from collaborative filtering and Bayesian optimization to search an enormous space of possible machine learning pipelines intelligently and efficiently.

The robot will go through an initial assessment phase to check on its overall health and the health of its instruments before it can move on to the deployment phase. Then, once its finally time to deploy its suite of instruments, that process alone is expected to take two to three months. InSight will place its seismometer, and only once the team is happy with its location and initial operations will it return to the deck to get its wind and thermal shields, which will sit atop the seismometer for protection. The lander will then pick up the heat probe to bring to the surface, before beginning its historic dig. Eventually, once it's all settled in, Barrett says we'll be'sitting back listening for Mars quakes.'

The UAE Minister of State for Artificial Intelligence Omar Sultan Al Olama said technologies are reshaping the energy scene globally. "Technology is going to change the impact of output and return in the energy scene globally. The factors are data, artificial intelligence and Internet of Things to name a few as well as block chain and other emerging technologies," Al Olama said at Adipec. "Through Artificial Intelligence, all sectors are changing. Any process that is algorithmic is being disrupted by this technology. And this disruption is retuning higher yields, increasing efficiency and improving safety and security. We can use data to drive faster and accurate decisions."